Maize-nutrient response information applied across Sub-Saharan Africa

被引:19
|
作者
Wortmann, Charles S. [1 ]
Milner, Maribeth [1 ]
Kaizzi, Kayuki C. [2 ]
Nouri, Maman [3 ]
Cyamweshi, Athanase R. [4 ]
Dicko, Mohammed K. [5 ]
Kibunja, Catherine N. [7 ]
Macharia, Martin [8 ]
Maria, Ricardo [9 ]
Nalivata, Patson C. [10 ]
Demissie, Negash [11 ]
Nkonde, Davy [6 ]
Ouattara, Korodjouma [12 ]
Senkoro, Catherine J. [13 ]
Tarfa, Bitrus Dawi [14 ]
Tetteh, Francis M. [15 ]
机构
[1] Univ Nebraska, Dept Agron & Hort, Lincoln, NE 68583 USA
[2] Natl Agr Res Labs, POB 7065, Kampala, Uganda
[3] INRAN, BP 240, Maradi, Niger
[4] Rwanda Agr Board, POB 5016, Kigali, Rwanda
[5] Inst Econ Rurale, BP 258,Rue Mohamed 5, Bamako, Mali
[6] ZARI, Mt Makulu Res Stn, Lusaka, Zambia
[7] KALRO Kabete, POB 14733-00800, Nairobi, Kenya
[8] CAB Int, POB 633-00621, Nairobi, Kenya
[9] IIAM, Av FPLM 2698,Caixa Postal 3658, Maputo, Mozambique
[10] Lilongwe Univ Agr & Nat Resources, Bunda Campus,POB 219, Lilongwe, Malawi
[11] Ethiopian Inst Agr Res, POB 2003, Addis Ababa, Ethiopia
[12] Inst Environm & Rech Agr INERA, O4 BP 8645, Ouagadougou, Burkina Faso
[13] Mlingano Agr Res Inst, POB 5088, Tanga, Tanzania
[14] Ahmadu Bello Univ, Fac Agr, Dept Soil Sci, Inst Agr Res, Zaria, Nigeria
[15] CSIR, Soil Res Inst, Acad Post Off, Kwadaso Kumasi, Ghana
关键词
Agroecological zones; Data queries; Extrapolation; Harvest Choice; Fertilizer use; Optimization; Recommendation domains; Smallholder;
D O I
10.1007/s10705-017-9827-0
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
The profit potential for a given investment in fertilizer use can be estimated using representative crop nutrient response functions. Where response data is scarce, determination of representative response functions can be strengthened by using results from homologous crop growing conditions. Maize (Zea mays L.) nutrient response functions were selected from the Optimization of Fertilizer Recommendations in Africa (OFRA) database of 5500 georeferenced response functions determined from field research conducted in Sub-Saharan Africa. Three methods for defining inference domains for selection of response functions were compared. Use of the OFRA Inference Tool (OFRA-IT) resulted in greater specificity of maize N, P, and K response functions with higher R-2 values indicating superiority compared with using the Harvest Choice Agroecological Zones (HC-AEZ) and the recommendation domains of the Global Yield Gap Atlas project (GYGA-RD). The OFRA-IT queries three soil properties in addition to climate-related properties while the latter two options use climate properties only. The OFRA-IT was generally insensitive to changes in criteria ranges of 20-25% used in queries suggesting value in using wider criteria ranges compared with the default for information scarce crop nutrient response functions.
引用
收藏
页码:175 / 186
页数:12
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